def test_next_window_time_sample_passed(self):
"""If next window time has elapsed with at least one sample passed then pass filtered value"""
test_window_scheme = WindowingScheme(self.window_test_filter, 3)
# Value 15 will be filtered as it ranges between lower and upper bound limits
filtered_value = test_window_scheme.filter(self.middle_value)
self.assertEquals(filtered_value, self.middle_value)
# Let next window time elapse
time.sleep(4)
filtered_value = test_window_scheme.filter(self.more_than_upper_bound)
# None is expected as filtered value because at least one sample has been already passed and
# value ranges outside lower and upper bound limits
self.assertEquals(filtered_value, None)
def test_next_window_time_sample_passed(self):
"""If next window time has elapsed with at least one sample passed then pass filtered value"""
test_window_scheme = WindowingScheme(self.window_test_filter, 3)
# Value 15 will be filtered as it ranges between lower and upper bound limits
filtered_value = test_window_scheme.filter(self.middle_value)
self.assertEquals(filtered_value, self.middle_value)
# Let next window time elapse
time.sleep(4)
filtered_value = test_window_scheme.filter(self.more_than_upper_bound)
# None is expected as filtered value because at least one sample has been already passed and
# value ranges outside lower and upper bound limits
self.assertEquals(filtered_value, None)
# Getting edge_system's network interface and disk name
network_interface = get_default_network_interface()
disk_name = get_disk_name()
# Filters to filter data at Sampling Functions
# Simple filters
cpu_pro_filter = RangeFilter(Type.CLOSED_REJECT, 5,
10) # If no of CPU processes <=5 or >=10
cpu_util_filter = RangeFilter(Type.AT_LEAST, None, 85) # CPU util >= 85
disk_usage_filter = RangeFilter(Type.AT_LEAST, None, 80) # Disk usage >= 80%
net_usage_filter = RangeFilter(Type.AT_LEAST, None,
1000000) # Network usage >= 1Mb
# Filter with windowing scheme
cpu_util_filter_with_window = WindowingScheme(cpu_util_filter, 30)
# ---------------------------------------------------------------------------
# User defined methods with RangeFilters
def read_cpu_procs():
cnt = cpu_stat.procs_running()
return cpu_pro_filter.filter(cnt)
def read_cpu_utilization(sample_duration_sec=1):
cpu_pcts = cpu_stat.cpu_percents(sample_duration_sec)
return cpu_util_filter_with_window.filter(
round((100 - cpu_pcts['idle']), 2))
execfile('sampleProp.conf', config)
# Getting edge_system's network interface and disk name
network_interface = get_default_network_interface()
disk_name = get_disk_name()
# Filters to filter data at Sampling Functions
# Simple filters
cpu_pro_filter = RangeFilter(Type.CLOSED_REJECT, 5, 10) # If no of CPU processes <=5 or >=10
cpu_util_filter = RangeFilter(Type.AT_LEAST, None, 85) # CPU util >= 85
disk_usage_filter = RangeFilter(Type.AT_LEAST, None, 80) # Disk usage >= 80%
net_usage_filter = RangeFilter(Type.AT_LEAST, None, 1000000) # Network usage >= 1Mb
mem_free_filter = RangeFilter(Type.AT_MOST, 15, None) # Memory Free <= 15%
# Filters with windowing scheme
net_usage_filter_with_window = WindowingScheme(net_usage_filter, 30)
mem_free_filter_with_window = WindowingScheme(mem_free_filter, 60)
# some standard metrics for Linux systems
# agent classes for different IoT system
# agent classes for different data center components
# agent classes for different kinds of of devices, connected to the IoT System
# we are showing here how to create a representation for a Device in IoTCC but
# using the notion of RAM (because we have no connected devices yet)
# agent classes for different kinds of layer 4/5 connections from agent to DCC
# -------User defined functions with filters for getting the next value for a metric --------
# usage of these shown below in main
# semantics are that on each call the function returns the next available value
# from the device or system associated to the metric.
def test_next_window_time_no_sample_passed(self):
"""If next window time has elapsed with no sample passed so far then pass collected value"""
test_window_scheme = WindowingScheme(self.window_test_filter, 3)
time.sleep(4)
collected_value = test_window_scheme.filter(self.more_than_upper_bound)
self.assertEquals(collected_value, self.more_than_upper_bound)
def test_window_filter(self):
"""If filter returns a valid value, windowing_scheme should return it"""
test_window_scheme = WindowingScheme(self.window_test_filter, 5)
filtered_value = test_window_scheme.filter(self.middle_value)
self.assertEquals(filtered_value, self.middle_value)
def test_init_windowing_scheme_window_size(self):
"""If window size is not a non negative number, raise ValueError"""
self.assertRaises(
ValueError, lambda: WindowingScheme(self.window_test_filter, "10"))
self.assertRaises(
ValueError, lambda: WindowingScheme(self.window_test_filter, -10))
def test_init_windowing_scheme_filter(self):
"""If filter not provided in Windowing scheme, raise TypeError"""
self.assertRaises(TypeError, lambda: WindowingScheme("", 10))
def test_next_window_time_no_sample_passed(self):
"""If next window time has elapsed with no sample passed so far then pass collected value"""
test_window_scheme = WindowingScheme(self.window_test_filter, 3)
time.sleep(4)
collected_value = test_window_scheme.filter(self.more_than_upper_bound)
self.assertEquals(collected_value, self.more_than_upper_bound)
def test_window_filter(self):
"""If filter returns a valid value, windowing_scheme should return it"""
test_window_scheme = WindowingScheme(self.window_test_filter, 5)
filtered_value = test_window_scheme.filter(self.middle_value)
self.assertEquals(filtered_value, self.middle_value)
from liota.lib.utilities.filters.range_filter import RangeFilter, Type
from liota.lib.utilities.filters.windowing_scheme.windowing_scheme import WindowingScheme
dependencies = ["iotcc"]
# Filters to filter data at Sampling Functions
# Simple filters
cpu_pro_filter = RangeFilter(Type.CLOSED_REJECT, 5,
10) # If no of CPU processes <=5 or >=10
cpu_util_filter = RangeFilter(Type.AT_LEAST, None, 85) # CPU util >= 85
disk_usage_filter = RangeFilter(Type.AT_LEAST, None, 80) # Disk usage >= 80%
net_usage_filter = RangeFilter(Type.AT_LEAST, None,
1000000) # Network usage >= 1Mb
# Filters with windowing scheme
net_usage_filter_with_window = WindowingScheme(net_usage_filter, 30)
# ---------------------------------------------------------------------------
# User defined methods with RangeFilters
def read_cpu_procs():
cnt = cpu_stat.procs_running()
return cpu_pro_filter.filter(cnt)
def read_cpu_utilization(sample_duration_sec=1):
cpu_pcts = cpu_stat.cpu_percents(sample_duration_sec)
return cpu_util_filter.filter(round((100 - cpu_pcts['idle']), 2))